First, library the package to access its functions. Use the tidyquant function, tq_get () to get the stock price data for Apple. Take a look at the data frame it returned. Plot the stock price over time. Calculate daily returns for the adjusted stock price using tq_mutate ().
Full Answer
How to retrieve historical stock prices in tidyquant?
We use the tidyquant function for all data retrieval. Set the parameter to tell tidyquant we want the historical stock prices. We can use the argument to pass a date as the start of the collection, which accepts character string in the form of “YYYY-MM-DD”.
Why should I use tidyquant?
With tidyquant all the benefits add up to one thing: a one-stop shop for serious financial analysis! Getting Financial Data from the web: tq_get (). This is a one-stop shop for getting web-based financial data in a “tidy” data frame format.
How do I use tidyquant in R?
The tidyquant package is focused on retrieving, manipulating, and scaling financial data analysis in the easiest way possible. To get the tidyquant package and start working with it, you first have to install it. This places it on your local computer. You then have to load it into your current R session.
What is included in the tidyquant package?
The tidyquant package includes several vignettes to help users get up to speed quickly: Blog Article: Excel in R - Pivot Tables, VLOOKUPs, and more!
What is crossover in trading?
Of particular interest is the crossover, the point at which a trend begins to emerge, which can be used as a buy or sell signal.
Can we use XY variants?
argument, but we can use the XY variant to accomplish the same task as the OHLC variant. The operation is the same except instead of
What is tq_get?
tq_get () is a consolidated function that gets data from various web sources. The function is a wrapper for several quantmod functions, Quandl functions, and also gets data from websources unavailable in other packages. The results are always returned as a tibble. The advantages are (1) only one function is needed for all data sources and (2) the function can be seemlessly used with the tidyverse: purrr, tidyr, and dplyr verbs.
Is tq_get_stock_index_options deprecated?
tq_get_stock_index_options () Is deprecated and will be removed in the next version. Please use tq_index_options () instead.
Table of Contents
See more on r-bloggers.com
Why Tidyquant?
- One of the reasons why I began my journey into R programming is because it’s the best open-source option for stock analysis. With quantitative financial analysis (QFA) packages like quantmodquantmod, xtsxts and TTRTTR, stock data can quickly be retrieved, sliced and diced, transformed and mutated, and visualized so I can make investment decisions. It’s really a beauti…
Benefits
- The tidyquanttidyquantphilosophy: 1. A few core functions with a lot of power, that 2. leverage the quantitative analysis power of xtsxts, quantmodquantmod and TTRTTR, and are 3. designed to be used and scaled with the tidyversetidyverse.
Example: Visualizing Moving Averages
- I’ll go through an example of visualizing the 15-day and 50-day moving averages of the stock symbol, AAPL, which is for Apple Inc. Moving averages are a popular trading tool that stock analysts use to determine buying and selling signals. According to Investopedia, the moving average is… Of particular interest is the crossover, the point at which a trend begins to emerge, …
Conclusion
- The tidyquanttidyquant package integrates the three primary QFA packages, quantmodquantmod, xtsxts, and TTRTTR, with the tidyversetidyverse.
Recap
- The purpose of this post was twofold: 1. Introduce you to the tidyquanttidyquantpackage 2. Show an example of the integration between the QFA packages and the tidyversetidyverse. We discussed why there is a need for tidyquanttidyquant, which is to help minimize the back and forth between xtsxts and tibbletibble (tidy dataframes). We also went through an example of getting s…
Further Reading
- tidyquant Vignette: This tutorial just scratches the surface of tidyquanttidyquant. The vignette explains much, much more!
- R for Data Science: A free book that thoroughly covers the tidyversetidyversepackages.
- Quantmod Website: Covers many of the quantmodquantmod functions. Also, see the quantmod vignette.
- tidyquant Vignette: This tutorial just scratches the surface of tidyquanttidyquant. The vignette explains much, much more!
- R for Data Science: A free book that thoroughly covers the tidyversetidyversepackages.
- Quantmod Website: Covers many of the quantmodquantmod functions. Also, see the quantmod vignette.
- Extensible Time-Series Website: Covers many of the xtsxts functions. Also, see the xts vignette.
